Methods and apparatus to credit media segments shared among multiple media assets

ABSTRACT

Methods, apparatus, systems and articles of manufacture to credit media segments shared among multiple media assets are disclosed. Example methods disclosed herein include comparing a sequence of monitored media signatures with a library of reference signatures to determine a signature match, the monitored media signatures representative of a monitored media presentation. Disclosed example methods also include determining duration and offset of the signature match, the offset to represent a position of the signature match relative to a start of a reference media asset associated with the signature match. Disclosed example methods further include crediting a segment of the monitored media presentation represented by the signature match to an identifier of a class of media assets including the reference media asset in response to a determination that (i) the duration of the signature match does not exceed a first threshold and (ii) the offset does not exceed a second threshold.

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent is a continuation of U.S. patent application Ser. No.16/888,203, filed on May 29, 2020. Priority to U.S. patent applicationSer. No. 16/888,203 is hereby claimed. U.S. patent application Ser. No.16/888,203 is hereby incorporated by reference in its entirety.

FIELD OF THE DISCLOSURE

This disclosure relates generally to media identification systems, and,more particularly, to methods and apparatus to credit media segmentsshared among multiple media assets.

BACKGROUND

A media monitoring entity can generate audio signatures from a mediasignal. Audio signatures are a condensed reference that can be used tosubsequently identify the media. These signatures can be hashed to allowfaster matching in an audio signature database. In some examples, amedia monitoring entity can monitor a media source feed (e.g., atelevision feed, etc.) to generate reference signatures representativeof media presented via that media source feed. Such reference signaturescan be compared to signatures generated by media monitors to creditviewership of the media.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example environment in which theteachings of this disclosure may be implemented.

FIG. 2 is a block diagram of an example implementation of a meter dataanalyzer included in the example environment of FIG. 1 .

FIG. 3 is a block diagram of an example implementation of a referencedatabase included in the example media data analyzer of FIG. 2 .

FIG. 4 is a flowchart representative of machine readable instructionswhich may be executed to implement the meter data analyzer of FIGS. 1and/or 2 .

FIG. 5 is a block diagram of an example processing platform structuredto execute the instructions of FIG. 4 to implement the meter dataanalyzer of FIGS. 1 and/or 2 .

The figures are not to scale. In general, the same reference numberswill be used throughout the drawing(s) and accompanying writtendescription to refer to the same or like parts.

Descriptors “first,” “second,” “third,” etc. are used herein whenidentifying multiple elements or components which may be referred toseparately. Unless otherwise specified or understood based on theircontext of use, such descriptors are not intended to impute any meaningof priority, physical order or arrangement in a list, or ordering intime but are merely used as labels for referring to multiple elements orcomponents separately for ease of understanding the disclosed examples.In some examples, the descriptor “first” may be used to refer to anelement in the detailed description, while the same element may bereferred to in a claim with a different descriptor such as “second” or“third.” In such instances, it should be understood that suchdescriptors are used merely for ease of referencing multiple elements orcomponents.

DETAILED DESCRIPTION

As used herein, the term “media” includes any type of content and/oradvertisement delivered via any type of distribution medium. Thus, mediaincludes television programming or advertisements, radio programming oradvertisements, movies, web sites, streaming media, etc.

Example methods, apparatus, and articles of manufacture disclosed hereinmonitor media presentations at media devices. Such media devices mayinclude, for example, Internet-enabled televisions, personal computers,Internet-enabled mobile handsets (e.g., a smartphone), video gameconsoles (e.g., Xbox®, PlayStation®), tablet computers (e.g., an iPad®),digital media players (e.g., a Roku® media player, a Slingbox®, etc.),etc.

In some examples, media monitoring information is aggregated todetermine ownership and/or usage statistics of media devices, determinethe media presented by the media devices, determine audience ratings,determine relative rankings of usage and/or ownership of media devices,determine types of uses of media devices (e.g., whether a device is usedfor browsing the Internet, streaming media from the Internet, etc.),and/or determine other types of media device information. In examplesdisclosed herein, monitoring information includes, but is not limitedto, one or more of media identifying information (e.g.,media-identifying metadata, codes, signatures, watermarks, and/or otherinformation that may be used to identify presented media), applicationusage information (e.g., an identifier of an application, a time and/orduration of use of the application, a rating of the application, etc.),identifying information (e.g., demographic information, a useridentifier, a panelist identifier, a username, etc.), etc.

Audio watermarking is a technique used to identify media, such astelevision broadcasts, radio broadcasts, advertisements (televisionand/or radio), downloaded media, streaming media, prepackaged media,etc. Existing audio watermarking techniques identify media by embeddingone or more audio codes (e.g., one or more watermarks), such as mediaidentifying information and/or an identifier that may be mapped to mediaidentifying information, into an audio and/or video component. In someexamples, the watermark is embedded in the audio or video component sothat the watermark is hidden. This embedding may be carried oututilizing psychoacoustic masking.

As used herein, the terms “code” or “watermark” are used interchangeablyand are defined to mean any identification information (e.g., anidentifier) that may be inserted or embedded in the audio or video ofmedia (e.g., a program or advertisement) for the purpose of identifyingthe media or for another purpose such as tuning (e.g., a packetidentifying header).

To identify watermarked media, the watermark(s) are extracted and usedto access a table of reference watermarks that are mapped to mediaidentifying information. In some examples, media monitoring companiesprovide watermarks and/or watermarking devices to media providers withwhich to encode their media source feeds. In some examples, if a mediaprovider provides multiple media source feeds (e.g., ESPN and ESPN 2,etc.), a media provider can provide a different watermark for each mediasource feed. In some examples, a media provider could encode a mediasource feed with an incorrect watermark (e.g., a watermark meant forESPN could accidentally be encoded on ESPN2, etc.). In this example,crediting using only watermarking could result in the wrong media sourcefeed being credited.

Unlike media monitoring techniques based on codes and/or watermarksincluded with and/or embedded in the monitored media, fingerprint orsignature-based media monitoring techniques generally use one or moreinherent characteristics of the monitored media during a monitoring timeinterval to generate a substantially unique proxy for the media Such aproxy is referred to as a signature or fingerprint, and can take anyform (e.g., a series of digital values, a waveform, etc.) representativeof any aspect(s) of the media signal(s) (e.g., the audio and/or videosignals forming the media presentation being monitored). A signature maybe a series of signatures collected in series over a time interval. Agood signature is repeatable when processing the same mediapresentation, but is unique relative to other (e.g., different)presentations of other (e.g., different) media. Accordingly, the terms“fingerprint” and “signature” are used interchangeably herein and aredefined herein to mean a proxy for identifying media that is generatedfrom one or more inherent characteristics of the media.

Signature-based media monitoring generally involves determining (e.g.,generating and/or collecting) signature(s) representative of a mediasignal (e.g., an audio signal and/or a video signal) output by amonitored media device and comparing the monitored signature(s) to oneor more reference signatures corresponding to known (e.g., reference)media source feeds. Various comparison criteria, such as across-correlation value, a Hamming distance, etc., can be evaluated todetermine whether a monitored signature matches a particular referencesignature. When a match between the monitored signature and a referencesignatures is found, the monitored media can be identified ascorresponding to the particular reference media represented by thereference signature that matched the monitored signature. In someexamples, signature matching is based on sequences of signatures suchthat, when a match between a sequence of monitored signatures and asequence of reference signatures is found, the monitored media can beidentified as corresponding to the particular reference mediarepresented by the sequence of reference signatures that matched thesequence of monitored signatures. Because attributes, such as anidentifier of the media, a presentation time, a broadcast channel, etc.,are collected for the reference signature, these attributes may then beassociated with the monitored media whose monitored signature(s) matchedthe reference signature(s). Example systems for identifying media basedon codes and/or signatures are long known and were first disclosed inThomas, U.S. Pat. No. 5,481,294, which is hereby incorporated byreference in its entirety.

Media monitoring entities (e.g., The Nielsen Company (US), LLC, etc.)desire knowledge regarding how users interact with media devices such assmartphones, tablets, laptops, smart televisions, etc. In particular,media monitoring entities want to monitor media presentations made atthe media devices to, among other things, monitor exposure toadvertisements, determine advertisement effectiveness, determine userbehavior, identify purchasing behavior associated with variousdemographics, etc. Media monitoring entities can provide media meters topeople (e.g., panelists) which can generate media monitoring data basedon the media exposure of those users. Such media meters can beassociated with a specific media device (e.g., a television, a mobilephone, a computer, etc.) and/or a specific person (e.g., a portablemeter, etc.).

Media monitoring entities can generate media reference databases thatcan include unhashed signatures, hashed signatures, and watermarks.These references are generated by a media monitoring entity (e.g., at amedia monitoring station (MMS), etc.) by monitoring a media source feed,identifying any encoded watermarks and determining signatures associatedwith the media source feed. In some examples, the media monitoringentity can hash the determined signatures. Additionally oralternatively, the media monitoring entities generate referencesignatures for downloaded reference media (e.g., from a streaming mediaprovider), reference media transmitted to the media monitoring entityfrom one or more media providers, etc. That is, the media monitoringentities can generate reference signatures of media that is not livebroadcasted. In some examples, media that is not live broadcastedincludes a subscription video on demand (SVOD) asset. As used herein, a“media asset” refers to any individual, collection, or portion/piece ofmedia of interest (e.g., a commercial, a song, a movie, an episode oftelevision show, etc.). Media assets can be identified via unique mediaidentifiers (e.g., a name of the media asset, a metadata tag, etc.).Media assets can be presented by any type of media presentation method(e.g., via streaming, via live broadcast, from a physical medium, etc.).

The reference database can be compared (e.g., matched, etc.) to mediamonitoring data (e.g., watermarks, unhashed signatures, hashedsignatures, etc.) gathered by mediameter(s) to allow crediting of mediaexposure. Monitored media can be credited using one, or a combination,of watermarks, unhashed signatures, and hashed signatures. Matchingusing signature matches of any length and/or timestamp (e.g., locationwithin signature) can generate false positives and incorrectly credit amedia exposure to media the panelist was not actually viewing. As usedherein, a “false positive” refers to incorrectly crediting a mediaexposure to a reference media asset that was not actually beingpresented to the panelist. For example, each episode of a televisionseries can include the same introduction segment including theme music,etc. As used herein, a “lead-in bumper” refers to a segment of mediathat is re-used in one or more media assets of a same category (e.g.,television episodes of the same series, movies of the same series,etc.). Thus, each episode of the television series will have a signaturesegment that is the same for each episode and which represents thelead-in bumper for that television series. If an episode is not in thereference database (e.g., a new episode in the series that does not yethave corresponding reference signatures stored in the referencedatabase), signature matching techniques may incorrectly credit adifferent episode based on the signature match corresponding to thelead-in bumper. To prevent incorrect matching caused by lead-in bumpers,methods, apparatus, and systems disclosed herein credit lead-in bumpersto a general identifier (e.g., a television series identifier, etc.),instead of individual episodes, thereby reducing incorrect crediting ofmedia exposures.

Although examples disclosed herein include crediting lead-in bumpers toa general identifier, examples disclosed herein are not limited thereto.For example, other examples of shared media (e.g., title sequencesand/or credit sequences of different episodes of the same series,commercial transitions that are shared among episodes of the sameseries, etc.) and/or any other media segments shared among multiplemedia assets can be credited to a general identifier.

In some examples, media monitoring entities store generated referencedatabases and gathered monitoring data on cloud storage services (e.g.,AMAZON WEB SERVICES®, etc.). To allow the crediting of time-shiftedviewing (e.g., viewing media via a digital video recorder (DVR), etc.),the stored references are retained for a period time after the initialpresentation of the media.

Methods and apparatus disclosed herein enable crediting media segmentsshared among multiple media assets. Example techniques disclosed hereininclude comparing a sequence of monitored media signatures with alibrary of reference signatures to determine a signature match, thesequence of monitored media signatures included in monitoring datacorresponding to a monitored media presentation. Disclosed exampletechniques also include determining a duration of the signature matchand determining an offset of the signature match, the offset torepresent a position of the signature match relative to a start of areference media asset associated with the signature match. Disclosedexample techniques further include crediting, in response to determining(i) the duration of the signature match does not exceed a durationthreshold and (ii) the offset does not exceed an offset threshold, asegment of the monitored media presentation represented by the signaturematch to an identifier of a class of media assets including thereference media asset.

FIG. 1 is a block diagram of an example environment 100 in which theteachings of this disclosure may be implemented. The example environment100 includes an example first media meter 102A, an example second mediameter 102B, and an example third media meter 102C, which output examplefirst monitoring data 104A, example second monitoring data 104B, andexample third monitoring data 104C, respectively, to an example network106. The environment 100 further includes an example data center 108,which includes an example meter data analyzer 110. In the illustratedexample, the meter data analyzer 110 outputs identification data 112 toan example media exposure creditor 114.

The example media meters 102A, 102B, 102C collect media monitoringinformation. In some examples, the media meters 102A, 102B, 102C areassociated with (e.g., installed on, coupled to, etc.) respective mediadevices. For example, a media device associated with one of the mediameters 102A, 102B, 102C presents media (e.g., via a display, etc.). Insome examples, the media device associated with one of the media meters102A, 102B, 102C additionally or alternatively presents the media onseparate media presentation equipment (e.g., speakers, a display, etc.).For example, the media device(s) associated with the media meters 102A,102B, 102C can include a personal computer, an Internet-enabled mobilehandsets (e.g., a smartphone, an iPod®, etc.), video game consoles(e.g., Xbox®, PlayStation 3, etc.), tablet computers (e.g., an iPad®, aMotorola™ Xoom™, etc.), digital media players (e.g., a Roku® mediaplayer, a Slingbox®, a Tivo®, etc.), televisions, desktop computers,laptop computers, servers, etc. In such examples, the media meters 102A,102B, 102C may have direct connections (e.g., physical connections) tothe devices to be monitored, and/or may be connected wirelessly (e.g.,via Wi-Fi, via Bluetooth, etc.) to the devices to be monitored.

Additionally or alternatively, in some examples, one or more of themedia meters 102A, 102B, 102C are portable meters carried by one or moreindividual people. In the illustrated example, the media meters 102A,102B, 102C monitor media presented to one or more people associated withthe media meters 102A, 102B, 102C and generate the example monitoringdata 104A, 104B, 104C. In some examples, monitoring data 104A, 104B,104C generated by the media meters 102A, 102B, 102C can includewatermarks detected in presented media. Such detected watermarks may bereferred to as monitored media watermarks or monitored watermarks asthey are detected in media monitored by the media meters 102A, 102B,102C. In some examples, the media meters 102A, 102B, 102C can determinesignatures associated with the presented media. For example, the mediameters 102A, 102B, 102C can determine signatures (e.g., generatesignatures, create signatures, etc.) representative of media presentedon the associated media devices. Such signatures may be referred to asmonitored media signatures or monitored signatures as they aredetermined from media monitored by the media meters 102A, 102B, 102C.Accordingly, the monitoring data 104A, 104B, 104C can include monitoredmedia signatures and/or monitored media watermarks representative of themedia monitored by the media meters 102A, 102B, 102C. In some examples,the monitoring data 104A, 104B, 104C is associated with a discrete,measurement time period (e.g., five minutes, ten minutes, etc.). In suchexample, the monitoring data 104A, 104B, 104C can include at sequencesof monitored media signatures and/or sequences of monitored mediawatermarks associated media asset(s) (or portions thereof) presented bythe media devices monitored by the media meters 102A, 102B, 102C.

Example signature generation techniques that may be implemented by themedia meters 102A, 102B, 102C include, but are not limited to, examplesdisclosed in U.S. Pat. No. 4,677,466 issued to Lert et al. on Jun. 30,1987; U.S. Pat. No. 5,481,294 issued to Thomas et al. on Jan. 2, 1996;U.S. Pat. No. 7,460,684 issued to Srinivasan on Dec. 2, 2008; U.S. Pat.No. 9,438,940 issued to Nelson on Sep. 6, 2016; U.S. Pat. No. 9,548,830issued to Kariyappa et al. on Jan. 17, 2017; U.S. Pat. No. 9,668,020issued to Nelson et al. on May 30, 2017; U.S. Pat. No. 10,200,546 issuedto Nelson et al. on Feb. 5, 2019; U.S. Publication No. 2005/0232411 toSrinivasan et al. published on Oct. 20, 2005; U.S. Publication No.2006/0153296 to Deng published on Jul. 13, 2006; U.S. Publication No.2006/0184961 to Lee et al. published on Aug. 17, 2006; U.S. PublicationNo. 2006/0195861 to Lee published on Aug. 31, 2006; U.S. Publication No.2007/0274537 to Srinivasan published on Nov. 29, 2007; U.S. PublicationNo. 2008/0091288 to Srinivasan published on Apr. 17, 2008; and U.S.Publication No. 2008/0276265 to Topchy et al. published on Nov. 6, 2008.

The example network 106 is a network used to transmit the monitoringdata 104A, 104B, 104C to the data center 108. In some examples, thenetwork 106 can be the Internet or any other suitable external network.In other examples, the network 106 can be a cable broadcast system andthe monitoring data 104A, 104B, 104C could be return path data (RPD). Inother examples, any other suitable means of transmitting the monitoringdata 104A, 104B, 104C to the data center 108 can be used.

The example data center 108 is an execution environment used toimplement the example meter data analyzer 110 and the example mediaexposure creditor 114. In some examples, the data center 108 isassociated with a media monitoring entity. In some examples, the datacenter 108 can be a physical processing center (e.g., a central facilityof the media monitoring entity, etc.). Additionally or alternatively,the data center 108 can be implemented via a cloud service (e.g., AWS®,etc.). In this example, the data center 108 can further store andprocess generated watermark and signature reference data.

The example meter data analyzer 110 processes the gathered mediamonitoring data to detect, identify, credit, etc., respective mediaassets and/or portions thereof (e.g., media segments) associated withthe corresponding monitoring data 104A, 104B, 104C. For example, themeter data analyzer 110 can compare the monitoring data 104A, 104B, 104Cto generated reference data to determine what respective media isassociated with the corresponding monitoring data 104A, 104B, 104C. Insome examples, the meter data analyzer 110 can hash the signaturesincluded in the monitoring data 104A, 104B, 104C. In some examples, themeter data analyzer 110 can identify the media by matching unhashedsignatures and/or hashed signatures. The meter data analyzer 110 of theillustrated example also analyzes the monitoring data 104A, 104B, 104Cto determine if the media asset(s), and/or particular portion(s) (e.g.,segment(s)) thereof, associated with the signature match is (are) to becredited. For example, the meter data analyzer 110 can compare monitoredmedia signatures in the monitoring data 104A, 104B, 104C to a library ofgenerated reference signatures to determine the media asset(s)associated with the monitored media signatures. In response to detectinga match between a sequence of the monitored media signatures and acorresponding sequence of the reference signatures, referred to hereinas a signature match, the meter data analyzer 110 can determine asignature match duration (e.g., the time duration associated with thesuccessive matches between the individual monitored media signatures andthe corresponding individual reference signatures included in thesignature match). In some examples, if the duration of the signaturematch is less than a duration threshold, the meter data analyzer 110determines the timestamp of the signature match with reference to thematched reference media asset. That is, the meter data analyzer 110 candetermine the time position within the matched reference media assetsthat is associated with the media segment represented by the signaturematch (e.g., where in the reference media asset the signature matchoccurred). In some examples, if the duration of the signature match isless than the duration threshold and occurs within a threshold timeperiod (e.g., an offset threshold), the meter data analyzer 110 candetermine whether to credit the segment of the monitored mediapresentation represented by the signature match as being associated witha lead-in bumper or other media segment shared among multiple mediaassets. For example, a signature match of a duration less than theduration threshold is representative of relatively short media segmentsthat are shared among multiple media assets (e.g., title sequence,credit sequence, etc. of television episodes, movies, etc.). Similarly,a signature match that occurs within the offset threshold isrepresentative of the position in the reference media asset the sharedmedia segment typically occurs. For example, a media segmentrepresenting a shared title sequence of a television series occurswithin an offset threshold from the start of the reference asset.Additionally or alternatively, a media segment representing a sharedcredit sequence of a television series occurs within an offset thresholdfrom the end of the reference asset. An example implementation of themeter data analyzer 110 is described below in conjunction with FIG. 2 .

The example identification data 112 includes information to credituser(s) associated with the media meters 102A, 102B, 102C with exposureto one or more particular media assets. For example, the identificationdata 112 can include direct associations between monitoring data 104A,104B, 104C and one or more particular media assets. For example, theidentification data 112 can include media identifiers associated withthe media assets represented in the monitoring data 104A, 104B, 104C andtimestamps associated with the period of exposure to that media. Theexample media exposure creditor 114 uses the identification data 112 tocredit media with having been exposed to user(s). In some examples, themedia exposure creditor 114 generates a report including data metricsthat may be presented to media providers.

FIG. 2 is a block diagram of an implementation of the meter dataanalyzer 110 of FIG. 1 . In the illustrated example, the meter dataanalyzer 110 includes an example network interface 202, an examplesignature matcher 204, an example reference database 206, an exampleduration determiner 208, an example offset determiner 210, an examplecredit determiner 212, and an example creditor interface 214.

The example network interface 202 allows the meter data analyzer 110 toreceive the monitoring data 104A, 104B, 104C from the example network106. In some examples, the network interface 202 can convert themonitoring data 104A, 104B, 104C into a format readable by the meterdata analyzer 110. In some examples, the network interface 202 can be incontinuous communication with the network 106, the first media meter102A, the second media meter 102B, and/or the third media meter 102C. Inother examples, the network interface 202 can be in intermittent (e.g.,periodic or aperiodic) communication with the network 106, the firstmedia meter 102A, the second media meter 102B, and/or the third mediameter 102C. In some examples, the network interface 202 can be absent.In such examples, the media meters 102A, 102B, 102C can be in directcommunication with the meter data analyzer 110. For example, if themeter data analyzer 110 is implemented via a cloud service, some or allof the media meters 102A, 102B, 102C can directly upload the monitoringdata 104A, 104B, 104C directly to the cloud service.

The example signature matcher 204 compares the monitored mediasignatures in the monitoring data 104A, 104B, 104C and the referencesignatures in the example reference database 206 to identify signaturematches. For example, the signature matcher 204 determines if a sequenceof the monitored signatures in the monitoring data 104A, 104B, 104Cmatches a sequence of reference signatures stored in the referencedatabase 206. In examples disclosed herein, the signature matcher 204may perform matching using any suitable means (e.g., unhashed matching,hashed matching, etc.) and/or comparison criteria, such as thosedescribed above. In some examples, the signature matcher 204 outputssignature match results that include a reference identifier identifyingthe reference media asset represented by the matched referencesignatures, a duration of the signature match corresponding to thelength of the matched media segment in the matched reference mediaasset, and a timestamp corresponding to a position (e.g., startingposition) of the matched media segment in the matched reference asset.

The example reference database 206 includes generated referencesignatures created or otherwise obtained by the data center 108. In someexamples, the reference database 206 includes reference unhashedsignatures and/or referenced hashed signatures. In some examples, themedia monitoring entity associated with the reference database 206 candirectly monitor media source feeds to generate reference unhashedsignatures and/or hashed signatures. In some examples, the mediamonitoring entity generates reference unhashed signatures and/or hashedsignatures from downloaded media (e.g., SVOD assets), etc. In examplesdisclosed herein, reference signatures are generated using the same orsimilar techniques as the monitored media signatures, such that themonitored media signatures and reference signatures of the same assetmatch. In some examples, each reference signature stored in thereference database 206 is associated with a specific reference mediaasset, such as, but not limited to, episodes of television programs(e.g., episodes of Game of Thrones, The Office, etc.), movies of a moviecollection (e.g., The Marvel Cinematic Universe, etc.), etc. In someexamples, each reference signature stored in the reference database 206is associated with a timestamp, which indicates a position in thereference media asset represented by the reference signature. In someexamples, the reference database 206 can include a library (e.g.,database, table, etc.) of reference hashed signatures.

The example duration determiner 208 determines a time duration of thesignature match or, in other words, the signature match duration betweena sequence of the monitored media signatures of the monitoring data104A, 104B, 104C and a corresponding sequence of the referencesignatures in the example reference database 206. For example, theduration determiner 208 can determine the signature match between agiven sequence of monitored media signatures in the monitoring data104A, 104B, 104C and the corresponding sequence of reference signaturerepresentative of a reference media asset covers the entire duration ofthe reference signatures associated with that reference media asset and,thus, the signature match covers the entire duration of the referencemedia asset. In some examples, the duration determiner 208 determinesthe time duration of the signature match based on timestamps associatedwith the first and last reference signatures of the signature match. Forexample, the timestamps associated with the first and last referencesignatures of the signature match correspond to positions in thereference asset. Thus, the duration determiner 208 may determine thetime duration of the signature match as the difference between thetimestamp of the last signature match and the timestamp of the firstsignature match of the reference asset. In some examples, the durationdeterminer 208 determines the signature match between the sequence ofmonitored signatures of the monitoring data 104A, 104B, 104C and thecorresponding sequence of reference signatures corresponds to a portion(e.g., a segment) of the reference asset.

The example offset determiner 210 determines the offset between asequence of monitored media signatures in the monitoring data 104A,104B, 104C and a corresponding matched sequence of reference signaturesrepresentative of a reference media asset. In some examples, the offsetdeterminer 210 determines the offset based on the timestamps associatedwith the signature matches of the reference signatures stored in thereference database 206. For example, the offset determiner 210determines the position of the signature match relative to the start ofthe reference media asset based on the corresponding timestamps of thefirst signature match and last signature match of the referencesignatures. In some examples, the offset determiner 210 determines thesignature match occurs in the first ten minutes of the reference asset.In some examples, the offset determiner 210 determines the signaturematch occurs relatively later in the reference asset (e.g., after 10minutes from the start of the reference asset).

The example credit determiner 212 generates the identification data 112based on the output of the duration determiner 208 and the offsetdeterminer 210. For example, the credit determiner 212 generatesidentification data 112 including a general identifier of a class ofmedia assets corresponding to the media segment match. That is, thegeneral identifier represents the class of media assets (e.g., atelevision series, a movie category, etc.) associated with the mediasegment match. Thus, the identification data 112 includes a generalidentifier that credits the class of media assets. For example, if theduration determiner 208 determines the signature match is less than aduration threshold (e.g., three minutes, two minutes, etc.) and theoffset determiner 210 determines the offset of the signature match ofthe media segment does not exceed an offset threshold (e.g., ten minutesfrom the start of the reference asset, eight minutes from the start ofthe reference asset, etc.), the credit determiner 212 generatesidentification data 112 indicating the monitoring data 104A, 104B, 104Ccorresponds to a class of media assets stored in the reference database206. That is, the identification data 112 associates the media exposureto a class of media (e.g., a television series, a movie series, etc.).In some examples, the credit determiner 212 determines the signaturematch exceeds the offset threshold. Thus, the credit determiner 212indicates signature coverage of the reference database 206 is notcomplete (e.g., a reference signature of the media exposure has not beengenerated and/or stored). The example creditor interface 214 transmitsthe identification data 112 to the media exposure creditor 114.

FIG. 3 is a block diagram of an example implementation of the referencedatabase 206 of FIG. 2 . The reference database 206 of FIG. 3 includesentries corresponding to an example episode 302, an example episode 304,and an example episode 306. In some examples, the episodes 302, 304, 306are episodes of the same television series (e.g., episodes of season 1of a television series, etc.). In the illustrated example, the episode302 is the first episode of a first television series, the episode 304is the second episode of the first television series, and the episode306 is the third episode of the first television series. The referencedatabase 206 includes an example sequence of reference signatures 303corresponding to the episode 302, an example sequence of referencesignatures 305 corresponding to the episode 304, and an example sequenceof reference signatures 307 corresponding to the episode 306. Thesequence of reference signatures 303, 305, 307 each include threesegments of signatures. However, the sequence of reference signatures303, 305, 307 can additionally or alternatively include any number ofsignature segments. In the illustrated example of FIG. 3 , the sequenceof reference signatures 303 includes an example unique signature segment308, an example bumper signature segment 310, and an example uniquesignature segment 312. The sequence of reference signatures 305 includesan example unique signature segment 314, the bumper signature segment310, and an example unique signature segment 316. The sequence ofreference signatures 307 includes an example unique signature segment318, the bumper signature segment 310, and an example unique signaturesegment 320. In some examples, the unique signature segments 308, 314,318 correspond to short signature segments (e.g., less than threeminutes, less than five minutes, etc.) to introduce the episodes 302,304, 306. In some examples, the unique signature segments 312,316,318correspond to the main content of the episodes 302, 304, 306.

While the sequence of reference signatures 303, 305, 307 in the exampleof FIG. 3 are illustrated as including three segments of signatures(e.g., the unique signature segments 308, 314, 318, the bumper signaturesegment 310, the unique signature segments 312,316,320), the referencesignatures may not be known to contain such segments. That is, thesequence of signatures 303, 305, 307 may not be divided and/or labeledas “unique” or “bumper” signature segments.

In the illustrated example of FIG. 3 , the bumper signature segment 310is a set of reference signatures corresponding to the shared lead-inbumper among multiple reference assets (e.g., the lead-in bumper of theepisodes 302, 304, 306 of season 1). In the illustrated example of FIG.3 , the unique signature segments 308,312,314,316,318,320 and the bumpersignature segment 310 are the same duration (e.g., the same number ofsignatures). However, the unique signature segments 308, 312, 314, 316,318, 320 and the bumper signature segment 310 can have any appropriateduration(s). For example, the signature segment 308 can be relativelyshorter than the signature segment 314. In such an example, the bumpersignature segment 310 of the sequence of reference signatures 303 has ashorter offset than the bumper signature segment 310 of the sequence ofreference signatures 305 (e.g., the offset determiner 210 determines theposition of the bumper signature segment 310 in the sequence ofreference signatures 303 is relatively closer to the beginning of thereference asset than the bumper signature segment 310 in the sequence ofreference signatures 305). Additionally or alternatively, the sequenceof reference signatures 303, 305, 307 can have different respectivedurations (e.g., include different numbers of signatures).

The illustrated example of FIG. 3 further includes an example sequenceof monitored media signatures 323 corresponding to the episode 322,which are not stored in the reference database 206. In some examples,the sequence of monitored media signatures 323 is included in themonitoring data 104A, 104B, 104C collected by the meters 102A, 102B,102C. For example, the episode 322 may be newly released (e.g., the datacenter 108 has not generated and stored the reference signature of theepisode 322). The episode 322 includes an example unique signaturesegment 324, the bumper signature segment 310, and an example uniquesignature segment 326. As described above, the sequence of monitoredmedia signatures 323 does not include the labels “unique” and “bumper”as the fact that the signature segments 324 and 326 are unique and thesignature segment 310 corresponds to the bumper signature segment maynot be known. In some examples, the signature matcher 204 compares thesequence of monitored media signatures 323 to the sequence of signatures303, 305, 307, and determines the bumper signature segment 310 of thesequence of monitored media signatures 323 matches the bumper signaturesegment 310 of the sequence of signatures 303, 305,307. The offsetdeterminer 210 determines the bumper signature 310 has a duration thatis less than the duration threshold. In some examples, the offsetdeterminer 210 determines the bumper signature segment 310 occurs withinthe offset threshold with respect to the start of the sequence ofreference signatures 303, 305, 307. In some such examples, the creditdeterminer 212 credits the media exposure of the episode 322 to anidentifier of the class of media assets corresponding to season 1 of theepisodes 302, 304, 306. Furthermore, in some such examples, such as whenthe other segments 324 and 326 do not match reference signature segments(e.g., such as the segments 308,312,314,316,318 and/or 320) in thereference database 206, the credit determiner 212 credits the mediaexposure of the episode 322 to the identifier of the class of mediaassets corresponding to season 1 of the episodes 302, 304, 306, but notto a specific one of the episodes. That is, the credit determiner 212credits the media exposure to the broader season (e.g., season 1) andnot the specific episodes 302, 304, 306.

While an example manner of implementing the meter data analyzer 110 ofFIG. 1 is illustrated in FIG. 2 , one or more of the elements, processesand/or devices illustrated in FIG. 2 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example network interface 202, the example signaturematcher 204, the example reference database 206, the example durationdeterminer 208, the example offset determiner 210, the example creditdeterminer 212, the example creditor interface 214 and/or, moregenerally, the example meter data analyzer 110 of FIG. 2 may beimplemented by hardware, software, firmware and/or any combination ofhardware, software and/or firmware. Thus, for example, any of theexample network interface 202, the example signature matcher 204, theexample reference database 206, the example duration determiner 208, theexample offset determiner 210, the example credit determiner 212, theexample creditor interface 214 and/or, more generally, the example meterdata analyzer 110 could be implemented by one or more analog or digitalcircuit(s), logic circuits, programmable processor(s), programmablecontroller(s), graphics processing unit(s) (GPU(s)), digital signalprocessor(s) (DSP(s)), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example, networkinterface 202, the example signature matcher 204, the example referencedatabase 206, the example duration determiner 208, the example offsetdeterminer 210, the example credit determiner 212, the example creditorinterface 214 and/or the example meter data analyzer 110 is/are herebyexpressly defined to include a non-transitory computer readable storagedevice or storage disk such as a memory, a digital versatile disk (DVD),a compact disk (CD), a Blu-ray disk, etc. including the software and/orfirmware. Further still, the example meter data analyzer 110 of FIG. 1may include one or more elements, processes and/or devices in additionto, or instead of, those illustrated in FIG. 2 , and/or may include morethan one of any or all of the illustrated elements, processes anddevices. As used herein, the phrase “in communication,” includingvariations thereof, encompasses direct communication and/or indirectcommunication through one or more intermediary components, and does notrequire direct physical (e.g., wired) communication and/or constantcommunication, but rather additionally includes selective communicationat periodic intervals, scheduled intervals, aperiodic intervals, and/orone-time events.

A flowchart representative of example hardware logic, machine readableinstructions, hardware implemented state machines, and/or anycombination thereof for implementing the meter data analyzer 110 of FIG.2 is shown in FIG. 4 . The machine readable instructions may be one ormore executable programs or portion(s) of an executable program forexecution by a computer processor such as the processor 512 shown in theexample processor platform 500 discussed below in connection with FIG. 5. The program may be embodied in software stored on a non-transitorycomputer readable storage medium such as a CD-ROM, a floppy disk, a harddrive, a DVD, a Blu-ray disk, or a memory associated with the processor512, but the entire program and/or parts thereof could alternatively beexecuted by a device other than the processor 512 and/or embodied infirmware or dedicated hardware. Further, although the example program isdescribed with reference to the flowchart illustrated in FIG. 4 , manyother methods of implementing the example meter data analyzer 110 mayalternatively be used. For example, the order of execution of the blocksmay be changed, and/or some of the blocks described may be changed,eliminated, or combined. Additionally or alternatively, any or all ofthe blocks may be implemented by one or more hardware circuits (e.g.,discrete and/or integrated analog and/or digital circuitry, an FPGA, anASIC, a comparator, an operational-amplifier (op-amp), a logic circuit,etc.) structured to perform the corresponding operation withoutexecuting software or firmware.

The machine readable instructions described herein may be stored in oneor more of a compressed format, an encrypted format, a fragmentedformat, a compiled format, an executable format, a packaged format, etc.Machine readable instructions as described herein may be stored as data(e.g., portions of instructions, code, representations of code, etc.)that may be utilized to create, manufacture, and/or produce machineexecutable instructions. For example, the machine readable instructionsmay be fragmented and stored on one or more storage devices and/orcomputing devices (e.g., servers). The machine readable instructions mayrequire one or more of installation, modification, adaptation, updating,combining, supplementing, configuring, decryption, decompression,unpacking, distribution, reassignment, compilation, etc. in order tomake them directly readable, interpretable, and/or executable by acomputing device and/or other machine. For example, the machine readableinstructions may be stored in multiple parts, which are individuallycompressed, encrypted, and stored on separate computing devices, whereinthe parts when decrypted, decompressed, and combined form a set ofexecutable instructions that implement a program such as that describedherein.

In another example, the machine readable instructions may be stored in astate in which they may be read by a computer, but require addition of alibrary (e.g., a dynamic link library (DLL)), a software development kit(SDK), an application programming interface (API), etc. in order toexecute the instructions on a particular computing device or otherdevice. In another example, the machine readable instructions may needto be configured (e.g., settings stored, data input, network addressesrecorded, etc.) before the machine readable instructions and/or thecorresponding program(s) can be executed in whole or in part. Thus, thedisclosed machine readable instructions and/or corresponding program(s)are intended to encompass such machine readable instructions and/orprogram(s) regardless of the particular format or state of the machinereadable instructions and/or program(s) when stored or otherwise at restor in transit.

The machine readable instructions described herein can be represented byany past, present, or future instruction language, scripting language,programming language, etc. For example, the machine readableinstructions may be represented using any of the following languages: C,C++, Java, C #, Perl, Python, JavaScript, HyperText Markup Language(HTML), Structured Query Language (SQL), Swift, etc.

As mentioned above, the example processes of FIG. 4 may be implementedusing executable instructions (e.g., computer and/or machine readableinstructions) stored on a non-transitory computer and/or machinereadable medium such as a hard disk drive, a flash memory, a read-onlymemory, a compact disk, a digital versatile disk, a cache, arandom-access memory and/or any other storage device or storage disk inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, for brief instances, for temporarily buffering,and/or for caching of the information). As used herein, the termnon-transitory computer readable medium is expressly defined to includeany type of computer readable storage device and/or storage disk and toexclude propagating signals and to exclude transmission media.

“Including” and “comprising” (and all forms and tenses thereof) are usedherein to be open ended terms. Thus, whenever a claim employs any formof “include” or “comprise” (e.g., comprises, includes, comprising,including, having, etc.) as a preamble or within a claim recitation ofany kind, it is to be understood that additional elements, terms, etc.may be present without falling outside the scope of the correspondingclaim or recitation. As used herein, when the phrase “at least” is usedas the transition term in, for example, a preamble of a claim, it isopen-ended in the same manner as the term “comprising” and “including”are open ended. The term “and/or” when used, for example, in a form suchas A, B, and/or C refers to any combination or subset of A, B, C such as(1) A alone, (2) B alone, (3) C alone, (4) A with B, (5) A with C, (6) Bwith C, and (7) A with Band with C. As used herein in the context ofdescribing structures, components, items, objects and/or things, thephrase “at least one of A and B” is intended to refer to implementationsincluding any of (1) at least one A, (2) at least one B, and (3) atleast one A and at least one B. Similarly, as used herein in the contextof describing structures, components, items, objects and/or things, thephrase “at least one of A or B” is intended to refer to implementationsincluding any of (1) at least one A, (2) at least one B, and (3) atleast one A and at least one B. As used herein in the context ofdescribing the performance or execution of processes, instructions,actions, activities and/or steps, the phrase “at least one of A and B”is intended to refer to implementations including any of (1) at leastone A, (2) at least one B, and (3) at least one A and at least one B.Similarly, as used herein in the context of describing the performanceor execution of processes, instructions, actions, activities and/orsteps, the phrase “at least one of A or B” is intended to refer toimplementations including any of (1) at least one A, (2) at least one B,and (3) at least one A and at least one B.

As used herein, singular references (e.g., “a”, “an”, “first”, “second”,etc.) do not exclude a plurality. The term “a” or “an” entity, as usedherein, refers to one or more of that entity. The terms “a” (or “an”),“one or more”, and “at least one” can be used interchangeably herein.Furthermore, although individually listed, a plurality of means,elements or method actions may be implemented by, e.g., a single unit orprocessor. Additionally, although individual features may be included indifferent examples or claims, these may possibly be combined, and theinclusion in different examples or claims does not imply that acombination of features is not feasible and/or advantageous.

The program 400 of FIG. 4 includes block 402. At block 402, the networkinterface 202 collects media meter data associated with a time period.For example, the network interface 202 allows the meter data analyzer110 to receive monitoring data 104A, 104B, 104C from the example network106. In some examples, the network interface 202 can convert thereceived monitoring data 104A, 104B, 104C into a format readable by themeter data analyzer 110.

At block 404, the signature matcher 204 identifies signature matches.For example, the signature matcher 204 compares the monitored mediasignatures in the monitoring data 104A, 104B, 104C to the referencesignatures stored in the reference database 206. In some examples, thesignature matcher 204 uses unhashed (e.g., linear) signature matching.In some examples, the signature matcher 204 uses hashed signaturematching.

At block 406, the duration determiner 208 determines the duration of thesignature match. For example, the duration determiner 208 determines thetimestamps associated with the first and last reference signature of thesignature match (e.g., the signature match determined at block 404) anddetermines the duration of the signature match based on the differencebetween the timestamps. At block 408, the duration determiner 208determines whether the signature match duration is greater than theduration threshold. In some examples, the duration threshold is threeminutes. Thus, the duration determiner 208 compares the signature matchduration to the duration threshold.

If, at block 408, the duration determiner 208 determines the signaturematch duration exceeds the duration threshold, then at block 410, thecredit determiner 212 credits the media exposure to the reference mediaasset associated with the reference signature match. For example, theduration determiner 208 determines the signature match duration coversthe entire duration of the reference signatures (e.g., the signaturematch duration is greater than three minutes). Thus, the creditdeterminer 212 generates identification data 112 crediting the referencemedia asset corresponding to signature match.

If, at block 408, the duration determiner 208 determines the signaturematch duration does not exceed the duration threshold, then at block412, the offset determiner 210 determines the offset between thetimestamps of the signature match and the start of the correspondingreference media asset. For example, the offset determiner 210 determinesthe timestamps of the reference signatures corresponding to the startand end of the signature match. In some examples, the offset determiner210 determines the signature match occurs within the first ten minutesof the reference asset).

At block 414, the offset determiner 210 determines whether the signaturematch occur within the offset threshold. In some examples, the offsetthreshold is ten minutes (e.g., the first ten minutes from the start ofthe reference asset). For example, the offset determiner 210 determineswhether the first and last timestamps of the reference signaturescorresponding to the signature match occur within the first ten minutesof the reference asset.

If, at block 414, the offset determiner 210 determines the signaturematch occurs within the offset threshold, then at block 416, the creditdeterminer 212 credits the media exposure associated with the signaturematch to the identifier of the class of media assets. That is, at block414, the credit determiner 212 credits the media exposure to the classof media assets (e.g., a television series, etc.) associated with thesignature match between the signatures of the monitoring data 104A,104B, 104C and the reference signatures. In some examples, the creditdeterminer 212 generates identification data 112 crediting theidentifier of the class of media assets. For example, the identifier ofthe class of media assets can correspond to a media category (e.g.,television series type, movie series type, etc.) of the signaturematches. For example, the credit determiner 212 credits the identifierof the television series associated with the signature match (e.g.,individual episodes of the television series are not credited). In someexamples, at block 414, the credit determiner 212 additionally oralternatively credits the media exposure associated with the signaturematch to a lead-in bumper (or other shared media segment) associatedwith that class of media assets.

If, at block 414, the offset determiner 210 determines the signaturematch does not occur within the offset threshold, then at block 418, thecredit determiner 212 indicates signature coverage is not complete. Thatis, the credit determiner 212 determines the media exposure does notmatch a single reference asset (e.g., a television episode, a movie,etc.) or a class of media assets (e.g., a television series, etc.). Forexample, the credit determiner 212 may generate identification data 112that does not credit any signatures stored in the reference database206.

At block 420, the meter data analyzer 110 determines whether to continuegenerating and/or analyzing signatures. If, at block 420, the meter dataanalyzer 110 determines to continue generating and/or analyzingsignatures, the program 400 returns to block 402. Otherwise, the program400 ends.

FIG. 5 is a block diagram of an example processor platform 500structured to execute the instructions of FIG. 4 to implement the meterdata analyzer 110 of FIGS. 1 and/or 2 . The processor platform 500 canbe, for example, a server, a personal computer, a workstation, aself-learning machine (e.g., a neural network), a mobile device (e.g., acell phone, a smart phone, a tablet such as an iPad™), a personaldigital assistant (PDA), an Internet appliance, a DVD player, a CDplayer, a digital video recorder, a Blu-ray player, a gaming console, apersonal video recorder, a set top box, a headset or other wearabledevice, or any other type of computing device.

The processor platform 500 of the illustrated example includes aprocessor 512. The processor 512 of the illustrated example is hardware.For example, the processor 512 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors, GPUs, DSPs, orcontrollers from any desired family or manufacturer. The hardwareprocessor may be a semiconductor based (e.g., silicon based) device. Inthis example, the processor implements the example network interface202, the example signature matcher 204, the example reference database206, the example duration determiner 208, the example offset determiner210, the example credit determiner 212, the example creditor interface214.

The processor 512 of the illustrated example includes a local memory 513(e.g., a cache). The processor 512 of the illustrated example is incommunication with a main memory including a volatile memory 514 and anon-volatile memory 516 via a bus 518. The volatile memory 514 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS® Dynamic Random Access Memory(RDRAM®) and/or any other type of random access memory device. Thenon-volatile memory 516 may be implemented by flash memory and/or anyother desired type of memory device. Access to the main memory 514, 516is controlled by a memory controller.

The processor platform 500 of the illustrated example also includes aninterface circuit 520. The interface circuit 520 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), a Bluetooth® interface, a near fieldcommunication (NFC) interface, and/or a PCI express interface.

In the illustrated example, one or more input devices 522 are connectedto the interface circuit 520. The input device(s) 522 permit(s) a userto enter data and/or commands into the processor 512. The inputdevice(s) can be implemented by, for example, an audio sensor, amicrophone, a camera (still or video), a keyboard, a button, a mouse, atouchscreen, a track-pad, a trackball, isopoint and/or a voicerecognition system.

One or more output devices 524 are also connected to the interfacecircuit 520 of the illustrated example. The output devices 524 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay (LCD), a cathode ray tube display (CRT), an in-place switching(IPS) display, a touchscreen, etc.), a tactile output device, a printerand/or speaker. The interface circuit 520 of the illustrated example,thus, typically includes a graphics driver card, a graphics driver chipand/or a graphics driver processor.

The interface circuit 520 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem, a residential gateway, a wireless access point, and/or a networkinterface to facilitate exchange of data with external machines (e.g.,computing devices of any kind) via a network 526. The communication canbe via, for example, an Ethernet connection, a digital subscriber line(DSL) connection, a telephone line connection, a coaxial cable system, asatellite system, a line-of-site wireless system, a cellular telephonesystem, etc.

The processor platform 500 of the illustrated example also includes oneor more mass storage devices 528 for storing software and/or data.Examples of such mass storage devices 528 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, redundantarray of independent disks (RAID) systems, and digital versatile disk(DVD) drives.

The machine executable instructions 532 of FIG. 4 may be stored in themass storage device 528, in the volatile memory 514, in the non-volatilememory 516, and/or on a removable non-transitory computer readablestorage medium such as a CD or DVD.

From the foregoing, it will be appreciated that example methods,apparatus and articles of manufacture have been disclosed that allow forreference signature matching. Example disclosed methods, apparatus andarticles of manufacture improve the efficiency of using a computingdevice by reducing computational and storage requirements of systemsthat identify media using signatures. For example, disclosed examplesprevent incorrect crediting and storage of partially matchingsignatures, which enables broader, more accurate crediting of media. Thedisclosed methods, apparatus and articles of manufacture are accordinglydirected to one or more improvement(s) in the functioning of a computer.

Example methods, apparatus, systems, and articles of manufacture tocredit media segments shared among multiple assets are disclosed herein.Further examples and combinations thereof include the following:

Example 1 includes an apparatus comprising a signature matcher tocompare a sequence of monitored media signatures with a library ofreference signatures to determine a signature match, the sequence ofmonitored media signatures representative of a monitored mediapresentation, a duration determiner to determine a duration of thesignature match, an offset determiner to determine an offset of thesignature match, the offset to represent a position of the signaturematch relative to a start of a reference media asset associated with thesignature match, and a credit determiner to credit a segment of themonitored media presentation represented by the signature match to anidentifier of a class of media assets including the reference mediaasset in response to a determination that (i) the duration of thesignature match does not exceed a first threshold and (ii) the offsetdoes not exceed a second threshold.

Example 2 includes the apparatus of example 1, wherein the creditdeterminer is to credit the monitored media presentation ascorresponding to the reference media asset in response to the durationof the signature match exceeding the first threshold.

Example 3 includes the apparatus of example 1, wherein the creditdeterminer is to indicate signature coverage is not complete and notcredit the identifier of the media asset in response to (i) the durationof the signature match not exceeding the first threshold and (ii) theoffset exceeding the second threshold.

Example 4 includes the apparatus of example 1, wherein the referencemedia asset is a first media asset, and the class of media assetsincludes the first media asset and a second media asset.

Example 5 includes the apparatus of example 1, wherein the durationdeterminer is to determine the duration of the signature match based ona difference between a first timestamp of the reference asset and asecond timestamp of the reference asset, the first timestampcorresponding to a first signature of the signature match and the secondtimestamp corresponding to a last signature of the signature match.

Example 6 includes the apparatus of example 1, wherein the mediapresentation is presented by a media device, and the sequence ofmonitored media signatures is included in monitoring data obtained froma meter that is to monitor the media device.

Example 7 includes the apparatus of example 1, wherein the firstthreshold is three minutes and the second threshold is ten minutes.

Example 8 includes a method comprising comparing, by executing aninstruction with a processor, a sequence of monitored media signatureswith a library of reference signatures to determine a signature match,the sequence of monitored media signatures representative of a monitoredmedia presentation, determining, by executing an instruction with theprocessor, a duration of the signature match, determining, by executingan instruction with the processor, an offset of the signature match, theoffset to represent a position of the signature match relative to astart of a reference media asset associated with the signature match,and crediting, by executing an instruction with the processor, a segmentof the monitored media presentation represented by the signature matchto an identifier of a class of media assets including the referencemedia asset in response to a determination that (i) the duration of thesignature match does not exceed a first threshold and (ii) the offsetdoes not exceed a second threshold.

Example 9 includes the method of example 8, further including creditingthe monitored media presentation as corresponding to the reference mediaasset in response to the duration of the signature match exceeding thefirst threshold.

Example 10 includes the method of example 8, further includingindicating signature coverage is not complete and not crediting theidentifier of the media asset in response to (i) the duration of thesignature match not exceeding the first threshold and (ii) the offsetexceeding the second threshold.

Example 11 includes the method of example 8, wherein the reference mediaasset is a first media asset, and the class of media assets include thefirst media asset and a second media asset.

Example 12 includes the method of example 8, further includingdetermining the duration of the signature match based on a differencebetween a first timestamp of the reference asset and a second timestampof the reference asset, the first timestamp corresponding to a firstsignature of the signature match and the second timestamp correspondingto a last signature of the signature match.

Example 13 includes the method of example 8, wherein the mediapresentation is presented by a media device, and the sequence ofmonitored media signatures is included in monitoring data obtained froma meter that is to monitor the media device.

Example 14 includes the method of example 8, wherein the first thresholdis three minutes and the second threshold is ten minutes.

Example 15 includes a non-transitory computer readable medium comprisinginstructions which, when executed, cause a machine to at least compare asequence of monitored media signatures with a library of referencesignatures to determine a signature match, the sequence of monitoredmedia signatures representative of a monitored media presentation,determine a duration of the signature match, determine an offset of thesignature match, the offset to represent a position of the signaturematch relative to a start of a reference media asset associated with thesignature match, and credit a segment of the monitored mediapresentation represented by the signature match to an identifier of aclass of media assets including the reference media asset in response toa determination that (i) the duration of the signature match does notexceed a first threshold and (ii) the offset does not exceed a secondthreshold.

Example 16 includes the non-transitory computer readable medium ofexample 15, wherein the instructions cause the machine to credit themonitored media presentation as corresponding to the reference mediaasset in response to the duration of the signature match exceeding thefirst threshold.

Example 17 includes the non-transitory computer readable medium ofexample 15, wherein the instructions cause the machine to indicatesignature coverage is not complete and not credit the identifier of themedia asset in response to (i) the duration of the signature match notexceeding the first threshold and (ii) the offset exceeding the secondthreshold.

Example 18 includes the non-transitory computer readable medium ofexample 15, wherein the reference media asset is a first media asset,and the class of media assets includes the first media asset and asecond media asset.

Example 19 includes the non-transitory computer readable medium ofexample 15, wherein the instructions cause the machine further todetermine the duration of the signature match based on a differencebetween a first timestamp of the reference asset and a second timestampof the reference asset, the first timestamp corresponding to a firstsignature of the signature match and the second timestamp correspondingto a last signature of the signature match.

Example 20 includes the non-transitory computer readable medium ofexample 15, wherein the media presentation is presented by a mediadevice, and the sequence of monitored media signatures representative isincluded in monitoring data obtained from a meter that is to monitor themedia device.

Example 21 includes the non-transitory computer readable medium ofexample 15, wherein the first threshold is three minutes and the secondthreshold is ten minutes.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

The following claims are hereby incorporated into this DetailedDescription by this reference, with each claim standing on its own as aseparate embodiment of the present disclosure.

1. An audience measurement computing system comprising: at least oneprocessor; a non-transitory computer readable medium having storedtherein instructions that, when executed by the at least one processor,cause performance of a set of operations, the operations comprising:determining a signature match duration associated with a matchedsequence of monitored media signatures based on multiple timestampsassociated with respective ones of one or more of: (i) the matchedsequence of monitored media signatures, or (ii) a corresponding sequenceof reference signatures that match the sequence monitored mediasignatures, wherein the sequence of monitored media signatures arerepresentative of a monitored media presentation, and wherein thecorresponding sequence of reference signatures are associated with areference media asset; determining an offset position of the matchedsequence of monitored media signatures relative to a start of thereference media asset; comparing the signature match duration to aduration threshold, and comparing the offset position to an offsetthreshold; making a determination, based on the comparing, that: (i) thesignature match duration satisfies the duration threshold; and (ii) theoffset position satisfies the offset threshold; and responsive to makingthe determination, crediting a class of media assets including thereference media asset with a media impression by an audiencecorresponding to the sequence of monitored media signatures, wherein theclass of media assets is a set of multiple individual media episodesthat each share a common segment, and wherein the reference media assetis one of the individual media episodes in the set of multipleindividual media episodes.
 2. The audience measurement computing systemof claim 1, wherein the operations further include: obtaining thesequence of monitored media signatures, the sequence of monitored mediasignatures from a monitored media exposure environment, the monitoredmedia exposure environment associated with the audience; and associatingthe credited media impression with an audience attribute associated withthe audience.
 3. The audience measurement computing system of claim 1,wherein the operations further include: comparing the sequence ofmonitored media signatures with a library of reference signatures, thelibrary of reference signatures including the corresponding sequence ofreference signatures; and determining, based on the comparing, that thesequence of monitored media signatures matches the correspondingsequence of reference signatures.
 4. The audience measurement computingsystem of claim 1, wherein the reference media asset is an individualepisode of a program series, and wherein the class of media assets isthe program series.
 5. The audience measurement computing system ofclaim 1, wherein the reference media asset is an individual movie of aseries of movies, and wherein the class of media assets is the series ofmovies.
 6. The audience measurement computing system of claim 1, whereinthe crediting the class of media assets with the media impression by theaudience includes crediting the class of media assets with a streamingmedia impression.
 7. The audience measurement computing system of claim1, wherein the duration threshold is satisfied by the signature matchduration being less than three minutes and wherein the offset thresholdis satisfied by an offset position being less than ten minutes.
 8. Amethod comprising: determining a signature match duration associatedwith a matched sequence of monitored media signatures based on multipletimestamps associated with respective ones of one or more of: (i) thematched sequence of monitored media signatures, or (ii) a correspondingsequence of reference signatures that match the sequence monitored mediasignatures, wherein the sequence of monitored media signatures arerepresentative of a monitored media presentation, and wherein thecorresponding sequence of reference signatures are associated with areference media asset; determining an offset position of the matchedsequence of monitored media signatures relative to a start of thereference media asset; comparing the signature match duration to aduration threshold, and comparing the offset position to an offsetthreshold; making a determination, based on the comparing, that: (i) thesignature match duration satisfies the duration threshold; and (ii) theoffset position satisfies the offset threshold; and responsive to makingthe determination, crediting a class of media assets including thereference media asset with a media impression by an audiencecorresponding to the sequence of monitored media signatures, wherein theclass of media assets is a set of multiple individual media episodesthat each share a common segment, and wherein the reference media assetis one of the individual media episodes in the set of multipleindividual media episodes.
 9. The method of claim 8, further including:obtaining the sequence of monitored media signatures, the sequence ofmonitored media signatures from a monitored media exposure environment,the monitored media exposure environment associated with the audience;and associating the credited media impression with an audience attributeassociated with the audience.
 10. The method of claim 8, furtherincluding: comparing the sequence of monitored media signatures with alibrary of reference signatures, the library of reference signaturesincluding the corresponding sequence of reference signatures; anddetermining, based on the comparing, that the sequence of monitoredmedia signatures matches the corresponding sequence of referencesignatures.
 11. The method of claim 8, wherein the reference media assetis an individual episode of a program series, and wherein the class ofmedia assets is the program series.
 12. The method of claim 8, whereinthe reference media asset is an individual movie of a series of movies,and wherein the class of media assets is the series of movies.
 13. Themethod of claim 8, wherein the crediting the class of media assets withthe media impression by the audience includes crediting the class ofmedia assets with a streaming media impression.
 14. The method of claim8, wherein the duration threshold is satisfied by the signature matchduration being less than three minutes and wherein the offset thresholdis satisfied by an offset position being less than ten minutes.
 15. Anon-transitory computer readable storage medium having stored thereininstructions that, when executed by at least one processor, causeperformance of: determining a signature match duration associated with amatched sequence of monitored media signatures based on multipletimestamps associated with respective ones of one or more of: (i) thematched sequence of monitored media signatures, or (ii) a correspondingsequence of reference signatures that match the sequence monitored mediasignatures, wherein the sequence of monitored media signatures arerepresentative of a monitored media presentation, and wherein thecorresponding sequence of reference signatures are associated with areference media asset; determining an offset position of the matchedsequence of monitored media signatures relative to a start of thereference media asset; comparing the signature match duration to aduration threshold, and comparing the offset position to an offsetthreshold; making a determination, based on the comparing, that: (i) thesignature match duration satisfies the duration threshold; and (ii) theoffset position satisfies the offset threshold; and responsive to makingthe determination, crediting a class of media assets including thereference media asset with a media impression by an audiencecorresponding to the sequence of monitored media signatures, wherein theclass of media assets is a set of multiple individual media episodesthat each share a common segment, and wherein the reference media assetis one of the individual media episodes in the set of multipleindividual media episodes.
 16. The non-transitory computer readablestorage medium of claim 15, wherein the instructions further cause, whenexecuted by the at least one processor, performance of: obtaining thesequence of monitored media signatures, the sequence of monitored mediasignatures from a monitored media exposure environment, the monitoredmedia exposure environment associated with the audience; and associatingthe credited media impression with an audience attribute associated withthe audience.
 17. The non-transitory computer readable storage medium ofclaim 15, wherein the instructions further cause, when executed by theat least one processor, performance of: comparing the sequence ofmonitored media signatures with a library of reference signatures, thelibrary of reference signatures including the corresponding sequence ofreference signatures; and determining, based on the comparing, that thesequence of monitored media signatures matches the correspondingsequence of reference signatures.
 18. The non-transitory computerreadable storage medium of claim 15, wherein the reference media assetis an individual episode of a program series, and wherein the class ofmedia assets is the program series.
 19. The non-transitory computerreadable storage medium of claim 15, wherein the crediting the class ofmedia assets with the media impression by the audience includescrediting the class of media assets with a streaming media impression.20. The non-transitory computer readable storage medium of claim 15,wherein the duration threshold is satisfied by the signature matchduration being less than three minutes and wherein the offset thresholdis satisfied by an offset position being less than ten minutes.